Physical Human-Robot Interaction Through Hugs with CASTOR Robot

Gaitan-Padilla, Maria; Maldonado-Mejía, Juan C.; Fonseca, Leodanis; Pinto-Bernal, Maria J.; Casas, Diego; Múnera, Marcela; Cifuentes, Carlos A.

doi:10.1007/978-3-030-90525-5_77

Cited by 7 publications

(3 citation statements)

References 8 publications

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“…This will account for an interaction that is a combination of multiple actions. (3) In the “release” step, we would apply touch or pressure signals in the hug release methods 37 .…”

Section: Discussionmentioning

confidence: 99%

“…To the best of our knowledge, the HUG taxonomy is the first well-defined taxonomy of hugs. Therefore, we compare the HUG taxonomy with the hugging behavior research (see 10,14,15,21,[24][25][26][27][28][29][30][31][32][33][34][35][36][37][38] ), covering the domain of humans and robots. Most reviews of the human hugging behavior research only suggest taxonomic ideas without conducting any further classification.…”

Section: Taxonomy Completenessmentioning

confidence: 99%

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A HUG taxonomy of humans with potential in human–robot hugs

Yan,

Wang,

Ren

et al. 2024

Sci Rep

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Humans can easily perform various types of hugs in human contact and affection experience. With the prevalence of robots in social applications, they would be expected to possess the capability of hugs as humans do. However, it is still not an easy task for robots, considering the complex force and spatial constraints of robot hugs. In this work, we propose the HUG taxonomy, which distinguishes between different hugging patterns based on human demonstrations and prior knowledge. In this taxonomy, hugs are arranged according to (1) hugging tightness, (2) hugging style, and (3) bilateral coordination, resulting in 16 different hug types. We then further study the hug type preference of humans in different scenarios and roles. Furthermore, we propose a rule-based classification system to validate the potential of this taxonomy in human–robot hugs based on a humanoid robot with an E-skin of contact sensation. The HUG taxonomy could provide human hugging behavior information in advance, facilitating the action control of humanoid robots. We believe the results of our work can benefit future studies on human–robot hugging interactions.

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“…This will account for an interaction that is a combination of multiple actions. (3) In the “release” step, we would apply touch or pressure signals in the hug release methods 37 .…”

Section: Discussionmentioning

confidence: 99%

Section: Taxonomy Completenessmentioning

confidence: 99%

A HUG taxonomy of humans with potential in human–robot hugs

Yan,

Wang,

Ren

et al. 2024

Sci Rep

View full text Add to dashboard Cite

show abstract

“…This emphasis on direct pHRI may be attributed to the fact that many of the applications that have emerged are socially oriented, as evidenced by the greater number of studies on non-functional touch compared to functional touch. For example, handshaking [59,60,71,77,78,80,83,85,87]; hugging [57,61,62,67,72]; clapping [27,54,55]; nursing [50,64,98,101,108]; and playing virtual games [19,38,94,111] [113] have received significant attention. This trend is consistent with the idea that touch can serve important social and emotional functions in HRI, which, in turn, contributes to the realization of the Society 5.0 vision to a certain extent.…”

Section: Direct Phrimentioning

confidence: 99%

Human Factors Considerations for Quantifiable Human States in Physical Human–Robot Interaction: A Literature Review

Abdulazeem,

2023

Sensors

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As the global population rapidly ages with longer life expectancy and declining birth rates, the need for healthcare services and caregivers for older adults is increasing. Current research envisions addressing this shortage by introducing domestic service robots to assist with daily activities. The successful integration of robots as domestic service providers in our lives requires them to possess efficient manipulation capabilities, provide effective physical assistance, and have adaptive control frameworks that enable them to develop social understanding during human–robot interaction. In this context, human factors, especially quantifiable ones, represent a necessary component. The objective of this paper is to conduct an unbiased review encompassing the studies on human factors studied in research involving physical interactions and strong manipulation capabilities. We identified the prevalent human factors in physical human–robot interaction (pHRI), noted the factors typically addressed together, and determined the frequently utilized assessment approaches. Additionally, we gathered and categorized proposed quantification approaches based on the measurable data for each human factor. We also formed a map of the common contexts and applications addressed in pHRI for a comprehensive understanding and easier navigation of the field. We found out that most of the studies in direct pHRI (when there is direct physical contact) focus on social behaviors with belief being the most commonly addressed human factor type. Task collaboration is moderately investigated, while physical assistance is rarely studied. In contrast, indirect pHRI studies (when the physical contact is mediated via a third item) often involve industrial settings, with physical ergonomics being the most frequently investigated human factor. More research is needed on the human factors in direct and indirect physical assistance applications, including studies that combine physical social behaviors with physical assistance tasks. We also found that while the predominant approach in most studies involves the use of questionnaires as the main method of quantification, there is a recent trend that seeks to address the quantification approaches based on measurable data.

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